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991.
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Cyclogenesis and long-fetched winds along the southeastern coast of South America may lead to floods in populated areas, as the Buenos Aires Province, with important economic and social impacts. A numerical model (SMARA) has already been implemented in the region to forecast storm surges. The propagation time of the surge in such extensive and shallow area allows the detection of anomalies based on observations from several hours up to the order of a day prior to the event. Here, we investigate the impact and potential benefit of storm surge level data assimilation into the SMARA model, with the objective of improving the forecast. In the experiments, the surface wind stress from an ensemble prediction system drives a storm surge model ensemble, based on the operational 2-D depth-averaged SMARA model. A 4-D Local Ensemble Transform Kalman Filter (4D-LETKF) initializes the ensemble in a 6-h cycle, assimilating the very few tide gauge observations available along the northern coast and satellite altimeter data. The sparse coverage of the altimeters is a challenge to data assimilation; however, the 4D-LETKF evolving covariance of the ensemble perturbations provides realistic cross-track analysis increments. Improvements on the forecast ensemble mean show the potential of an effective use of the sparse satellite altimeter and tidal gauges observations in the data assimilation prototype. Furthermore, the effects of the localization scale and of the observational errors of coastal altimetry and tidal gauges in the data assimilation approach are assessed.  相似文献   
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The Paulistana and Santa Filomena Complexes are situated in the southern part of the Borborema Province (northeastern Brazil), in the Riacho do Pontal Orogen, and represent meta-volcano-sedimentary sequences. We present compositional variations in the metasedimentary rocks and new U–Pb detrital zircon data. Major and trace elements indicate that the metasedimentary rocks from the Paulistana and Santa Filomena Complexes are composed mostly of immature to mature sediments derived from felsic-intermediate sources with moderate to slightly high chemical weathering. The geochemical signatures of the sediment protoliths for both complexes are characteristic of continental magmatic arc settings with minor contribution from recycled sediment sources. The source area for the Paulistana Complex rocks follow the compositional trend between calc-alkaline granites and granodiorites, whereas the Santa Filomena Complex rocks have a more restricted composition trending to more granodioritic sources. For the Paulistana Complex, two main source ages were identified: (1) Tonian (ca. 950 Ma – sample RPE-58) and Tonian–Stenian (ca. 1.0 Ga – sample RPE-103). These data coupled with geochemical information suggest that the Cariris Velhos arc system was the main source area for the Paulistana Complex. Regarding the Santa Filomena metasedimentary rocks, potential source-areas include: (1) Neoarchaean rocks (~2.6 Ga) represented by the adjacent basement rocks of the Riacho do Pontal Orogen; (2) Rhyacian–Orosirian rocks (2.2–2.0 Ga) of the Riacho do Pontal Orogen and the Pernambuco–Alagoas terrain, which include an augen-gneiss with arc-related geochemical signature; (3) Statherian granites (1.7–1.6 Ga); and (4) Cariris Velhos crust (1000–920 Ma). The metasedimentary rocks of the Paulistana Complex were deposited in a rift stage (ca. 900 Ma), which is related to the break-up of the Rodinia supercontinent. The metasedimentary rocks of the Santa Filomena Complex most probably were deposited in another rift stage (ca. 750–700 Ma) and could be correlatives of the rift formation of the Canindé Domain (Sergipano Orogen).  相似文献   
998.
The present study analysed the taphonomic characteristics of small mammal bone accumulations produced by small felids in an area from the central Monte Desert (Mendoza, Argentina). In order to provide criteria to identify the role that these predators had in the formation of zooarchaeological assemblages, the anatomical representation, bone breakage patterns and degrees of digestive corrosion were evaluated. The main taphonomic results are: low average values for the relative abundance of skeletal elements; greater representation of mandibles, maxillae, isolated incisors, humeri and femora than the remaining elements; preponderance of cranial elements with high proportion of isolated teeth; elevated frequencies of proximal limb bones compared with distal parts; high degree of breakage in all skeletal elements and digestive corrosion on almost all diagnostic bones (mainly moderate and heavy). The values of the studied taphonomic variables indicate that small felids in this area made severe alterations to the bones of their prey (mainly rodents), attributable to the category of extreme modifier, while preserving enough skeletal elements to allow their taphonomic characterization. Tooth marks or grooves on bone surfaces produced by scratching and chewing were not detected. The low relative abundance of skeletal elements, the high degree of breakage and the elevated frequency of elements with digestion traces represent general taphonomic patterns that fall within those reported for other South American small carnivores.  相似文献   
999.
The accuracies of three different evolutionary artificial neural network (ANN) approaches, ANN with genetic algorithm (ANN-GA), ANN with particle swarm optimization (ANN-PSO) and ANN with imperialist competitive algorithm (ANN-ICA), were compared in estimating groundwater levels (GWL) based on precipitation, evaporation and previous GWL data. The input combinations determined using auto-, partial auto- and cross-correlation analyses and tried for each model are: (i) GWL t?1 and GWL t?2; (ii) GWL t?1, GWL t?2 and P t ; (iii) GWL t?1, GWL t?2 and E t ; (iv) GWL t?1, GWL t?2, P t and E t ; (v) GWL t?1, GWL t?2 and P t?1 where GWL t , P t and E t indicate the GWL, precipitation and evaporation at time t, individually. The optimal ANN-GA, ANN-PSO and ANN-ICA models were obtained by trying various control parameters. The best accuracies of the ANN-GA, ANN-PSO and ANN-ICA models were obtained from input combination (i). The mean square error accuracies of the ANN-GA and ANN-ICA models were increased by 165 and 124% using ANN-PSO model. The results indicated that the ANN-PSO model performed better than the other models in modeling monthly groundwater levels.  相似文献   
1000.
Hurricanes and tropical storms represent one of the major hazards in coastal communities. Storm surge generated by strong winds and low pressure from these systems have the potential to bring extensive flooding in coastal areas. In many cases, the damage caused by the storm surge may exceed the damage from the wind resulting in the total collapse of buildings. Therefore, in coastal areas, one of the sources for major structural damage could be due to scour, where the soil below the building that serves as the foundation is swept away by the movement of the water. The existing methodologies to forecast hurricane flood damage do not differentiate between the different damage mechanisms (e.g., inundation vs. scour). Currently, there are no tools available that predominantly focus on forecasting scour-related damage for buildings. Such a tool could provide significant advantages for planning and/or preparing emergency responses. Therefore, the focus of this study was to develop a methodology to predict possible scour depth due to hurricane storm surges using an automated ArcGIS tool that incorporates the expected hurricane conditions (flow depth, velocity, and flood duration), site-specific building information, and the associated soil types for the foundation. A case study from Monmouth County (NJ), where the scour damages from 2012 Hurricane Sandy were recorded after the storm, was used to evaluate the accuracy of the developed forecasting tool and to relate the scour depth to potential scour damage. The results indicate that the developed tool provides relatively consistent results with the field observations.  相似文献   
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